{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3553bd73-ec5d-4067-9cd1-3940e224dc60",
   "metadata": {
    "id": "XIyP_0r6zuVc"
   },
   "source": [
    "<!-- Banner Image -->\n",
    "<img src=\"https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/brevdevnotebooks.png\" width=\"100%\">\n",
    "\n",
    "<!-- Links -->\n",
    "<center>\n",
    "  <a href=\"https://console.brev.dev\" style=\"color: #06b6d4;\">Console</a> •\n",
    "  <a href=\"https://brev.dev\" style=\"color: #06b6d4;\">Docs</a> •\n",
    "  <a href=\"/\" style=\"color: #06b6d4;\">Templates</a> •\n",
    "  <a href=\"https://discord.gg/NVDyv7TUgJ\" style=\"color: #06b6d4;\">Discord</a>\n",
    "</center>\n",
    "\n",
    "# Export your Fine-Tuned Model to GGUF to Run Locally 🤙\n",
    "\n",
    "Welcome!\n",
    "\n",
    "We will export a checkpoint from our fine-tuned model ([Fine-tune Mistral 7B on your own data](), [Fine-tune Mistral 7B on HF dataset](), [Fine-tune Llama 2 on your own data]()) to a GGUF (the updated version of GGML) file. This will allow you to run your model locally, on your CPU, and/or on any GPUs your machine may have. You can also upload it to local LLM UI applications like [Ollama](https://ollama.ai/).\n",
    "\n",
    "### Help us make this tutorial better! Please provide feedback on [Discord](https://discord.gg/NVDyv7TUgJ) or on [X](https://x.com/harperscarroll)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c1354c7-c117-489d-897e-abb989f88f14",
   "metadata": {
    "id": "hWI-uRLEyRgb"
   },
   "source": [
    "## Let's begin!\n",
    "\n",
    "I used a GPU and dev environment from [brev.dev](https://brev.dev). Click the badge below to get your preconfigured instance:\n",
    "\n",
    "[![ Click here to deploy.](https://uohmivykqgnnbiouffke.supabase.co/storage/v1/object/public/landingpage/brevdeploynavy.svg)](https://console.brev.dev/environment/new?instance=A10G:g5.xlarge&diskStorage=256&name=gguf-export&file=https://github.com/brevdev/notebooks/raw/main/gguf-export.ipynb&python=3.10&cuda=12.0.1)\n",
    "\n",
    "Once you've checked out your machine and landed in your instance page, select the specs you'd like (I used Python 3.10 and CUDA 12.0.1; these should be preconfigured for you if you use the badge above) and click the \"Build\" button to build your verb container. Give this a few minutes.\n",
    "\n",
    "A few minutes after your model has started Running, click the 'Notebook' button on the top right of your screen once it illuminates (you may need to refresh the screen). You will be taken to a Jupyter Lab environment, where you can upload this Notebook.\n",
    "\n",
    "Note: You can connect your cloud credits (AWS or GCP) by clicking \"Org: \" on the top right, and in the panel that slides over, click \"Connect AWS\" or \"Connect GCP\" under \"Connect your cloud\" and follow the instructions linked to attach your credentials."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7245daac-c4ed-4d52-8de6-5376232bdf98",
   "metadata": {},
   "source": [
    "## 1. Save Model, Tokenizer, and LoRA Checkpoint\n",
    "First, we want to create a script to save the model, tokenizer, and LoRA checkpoint (which you have uploaded) to a file that we can then transform to GGUF."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ff85a597-a285-418c-b453-d133e92dfdc4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "!pip install transformers torch torchvision torchaudio peft accelerate sentencepiece gguf\n",
    "!pip install -U git+https://github.com/huggingface/peft.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0bcd661e-86ed-468c-b1cc-a995d491c9c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting save_model.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile save_model.py\n",
    "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
    "from peft import PeftModel\n",
    "import os\n",
    "import torch\n",
    "import argparse\n",
    " \n",
    "def main():\n",
    " \n",
    "    parser = argparse.ArgumentParser()\n",
    "    parser.add_argument(\"--model\", type=str)\n",
    "    parser.add_argument(\"--lora\", type=str)\n",
    "    parser.add_argument(\"--out_dir\", type=str, default=\"./model\") # leave this\n",
    "    args = parser.parse_args()\n",
    " \n",
    "    print(f\"Loading base model: {args.model}\")\n",
    "    base_model = AutoModelForCausalLM.from_pretrained(args.model, torch_dtype=torch.float16, device_map=\"auto\")\n",
    " \n",
    "    print(f\"Loading PEFT: {args.lora}\")\n",
    "    model = PeftModel.from_pretrained(base_model, args.lora)\n",
    "    print(f\"Running merge_and_unload\")\n",
    "    model = model.merge_and_unload()\n",
    "    tokenizer = AutoTokenizer.from_pretrained(args.model)\n",
    " \n",
    "    model.save_pretrained(f\"{args.out_dir}\")\n",
    "    tokenizer.save_pretrained(f\"{args.out_dir}\")\n",
    "    print(f\"Model saved to {args.out_dir}\")\n",
    " \n",
    "if __name__ == \"__main__\" :\n",
    "    main()"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "e1920253-4d06-41bd-ab72-4d1af423ef61",
   "metadata": {},
   "source": [
    "Next, we run the script. Replace `mistralai/Mistral-7B-v0.1` and `checkpoint-500` below with the names of the correct Hugging Face base model, and your appropriate checkpoint number. Recall the `checkpoint-[STEP#]` directory should look like this:\n",
    "\n",
    "![image.png](attachment:df5153b6-39bf-4b8e-9c3c-a2dbca94bbde.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ff85a597-a285-418c-b453-d133e92dfdc4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading base model: mistralai/Mistral-7B-v0.1\n",
      "Loading checkpoint shards: 100%|██████████████████| 2/2 [01:58<00:00, 59.32s/it]\n",
      "Loading PEFT: checkpoint-500\n",
      "Running merge_and_unload\n",
      "Model saved to ./model\n"
     ]
    }
   ],
   "source": [
    "!python save_model.py --model 'mistralai/Mistral-7B-v0.1' --lora 'checkpoint-500' "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4e580b8-f10d-493b-8b36-45125123cfd5",
   "metadata": {},
   "source": [
    "## 2. Convert to GGUF \n",
    "Now we convert to GGUF using the `llama.cpp` `convert.py` script."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "119c11a7-26dd-4e3b-890b-4aa912d8a204",
   "metadata": {},
   "outputs": [],
   "source": [
    "!curl -L -o convert.py https://github.com/ggerganov/llama.cpp/raw/master/convert.py\n",
    "!curl -L -o requirements.txt https://github.com/ggerganov/llama.cpp/raw/master/requirements.txt\n",
    "\n",
    "!pip install -r requirements.txt\n",
    "\n",
    "# Convert the 7B model to ggml FP16 format\n",
    "!python3 convert.py model\n",
    "\n",
    "## Code below is optional - uncomment (remove leftmost '# ') to use\n",
    "\n",
    "# # [Optional] for models using BPE tokenizers\n",
    "# !python convert.py model --vocabtype bpe\n",
    "\n",
    "# # [Optional] quantize the model to 4-bits (using q4_0 method)\n",
    "# !./quantize ./model/ggml-model-f16.gguf ./model/ggml-model-q4_0.gguf q4_0\n",
    "\n",
    "# # [Optional] update the gguf filetype to current if older version is unsupported by another application\n",
    "# !./quantize ./model/ggml-model-q4_0.gguf ./model/ggml-model-q4_0-v2.gguf COPY"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "833bdbd6-7699-4de9-9cf5-a20cd2abfe61",
   "metadata": {},
   "source": [
    "### Excellent! Now you have the GGUF file. \n",
    "This can be uploaded to Oobabooga (an LLM user interface, akin to Stable Diffusion's AUTOMATIC1111) - see tutorial [here](https://github.com/brevdev/notebooks/blob/main/oobabooga.ipynb) - or you can run from the command line using [Ollama](https://ollama.ai/). For Ollama instructions, click [here](https://github.com/jmorganca/ollama#customize-your-own-model)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eee27a9c-b1aa-460a-8e04-437f7ea19f36",
   "metadata": {},
   "source": [
    "## 3. Optional: Save to your Local Machine\n",
    "\n",
    "If you'd like to download the model to your local machine, open up your favorite shell on your local machine (or choose the application \"Terminal\" if you're not familiar) and enter the command:\n",
    "\n",
    "`scp ubuntu@export-ggml:~/model/ggml-model-f16.gguf ~/Desktop`\n",
    "\n",
    "This assumes an instance name `export-ggml`, the gguf file is named `ggml-model-f16.gguf` and it is in a `model` directory within your home directory, and you'd like to save it to your local Desktop. **This download will take a while, probably a few hours.**\n",
    "\n",
    "Great! Now you've downloaded the `gguf` file for your fine-tuned model, which you can run locally on your machine. Again, services like [Ollama](https://ollama.ai/) are great for this. \n"
   ]
  },
  {
   "cell_type": "markdown",
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    "## I hope you enjoyed this tutorial!\n",
    "\n",
    "I hope you enjoyed this tutorial on downloading your fine-tuned model as a GGUF file. If you have any questions, feel free to reach out to me on [X](https://x.com/harperscarroll) or on [Discord](https://discord.gg/NVDyv7TUgJ).\n",
    "\n",
    "🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙 🤙"
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